Robotic process automation (RPA) has been established for years. Now AI agents promise to take over tasks even more flexibly. But which technology fits which problem? A sober comparison.
How RPA works
RPA bots imitate human clicks and keystrokes in user interfaces. They follow precisely defined rules: open program A, copy field B, paste it into program C. That is fast, cheap to run and fully predictable – as long as nothing changes.
How AI agents work
AI agents are built on language models. They understand goals in natural language, interpret unstructured content, plan intermediate steps and call tools through interfaces such as APIs or MCP servers. That lets them cope with variations, exceptions and free text.
Side by side
| Criterion | RPA | AI agent |
|---|---|---|
| Input | Structured, consistent | Also unstructured: emails, PDFs, free text |
| Flexibility | Breaks when the interface changes | Adapts to variations |
| Predictability | Very high | High – with tests, guardrails and approvals |
| Cost per run | Very low | Depends on model and scope |
| Ideal for | Stable, rule-based high-volume tasks | Knowledge work with interpretation and exceptions |
When RPA is the better choice
- The process is entirely rule-based and rarely changes.
- Input always has the same structure.
- Volumes are very high and every cent per run counts.
When an AI agent is the better choice
- Input is unstructured or varies a lot.
- The task requires understanding, summarising or writing.
- The workflow requires decisions based on context.
- Automation has failed so far because of too many exceptions.
The combination is often strongest
In practice, both approaches complement each other. An AI agent reads a free-text order, extracts the line items and decides whether follow-up questions are needed. A classic workflow or direct API integration then handles the structured transfer into the ERP. That way you use AI’s flexibility where it is needed and the efficiency of rule-based automation everywhere else.
Conclusion
RPA is a precise tool for stable routines; AI agents are flexible co-workers for knowledge work. The question is rarely “either/or” but “which tool for which job”. We help you find the right mix for your processes.